PROJECT SUMMARY
Invasive aspergillosis is one of the most common fungal infections in immunocompromised patients. With
the increasing number of susceptible patients and the threat of antifungal-resistance, the development of host-
centric interventions is of paramount importance. Complement, a potent component of the innate immune
system, is protective against many infections. On the other hand, complement overactivation has been shown
to drive lung injury and inflammation. Pulmonary hemorrhage is a characteristic feature of invasive aspergillosis,
and the interactions between pulmonary hemorrhage and complement activation are poorly understood.
Intervening in the interactions between hemorrhage and complement may prove beneficial as a novel therapeutic
intervention to manage pulmonary aspergillosis, and a number of complement inhibitors are either FDA-
approved or in late-phase development.
The overarching hypothesis in this project is that pulmonary hemorrhage in invasive aspergillosis
leads to complement overactivation, leading to tissue injury and further hemorrhage. The dynamics of
complement activation are complex and span multiple sites, making it difficult to predict how and when to
intervene. We propose that mathematical modeling-based design of effective therapies in pulmonary
aspergillosis can help in the discovery phase of understanding mechanisms of complement-mediated injury in
pulmonary aspergillosis, and possible interventions of such mechanisms. As such we will leverage the power of
mathematical modeling, closely coupled with in vivo models of pulmonary aspergillosis, to unravel the
interactions of hemorrhage and complement in the lung and to systematically interrogate the model to determine
possible points of intervention. In Aim 1, we will mechanistically explore the effects of the terminal component of
the complement cascade in pulmonary aspergillosis. In Aim 2, we will build a multiscale mathematical model of
pulmonary aspergillosis to capture the mechanisms that connect hemorrhage and complement activity, validating
these mechanisms in vivo. We will then use the model to derive a prioritized set of interventions that will be
validated in mouse models of pulmonary aspergillosis.
This research is intended to train a PhD mathematician with a background in mathematical modeling in
experimental biology and facilitate his transition to an independent investigator. He will be mentored by a
physician-scientist with expertise in lung host defense and a complement biologist and overseen by an advisory
committee composed of experts in computational modeling, lung biology, and mycology. This training will be
enhanced by the rich scientific environment at the University of Florida, together with rigorous coursework in
advanced immunology, mycology, and microbiology, and training in grant writing and scientific rigor. Taken
together, this project will train a transdisciplinary scientist for an independent investigative career.